J

mcp-perplexity-search

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Created 1/22/2025byspences10

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mcpmodel-context-protocolperplexitysearch

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JavaScript

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mcp-perplexity-search

A Model Context Protocol (MCP) server for integrating Perplexity's AI API with LLMs. This server provides advanced chat completion capabilities with specialized prompt templates for various use cases.

Features

  • 🤖 Advanced chat completion using Perplexity's AI models
  • 📝 Predefined prompt templates for common scenarios:
    • Technical documentation generation
    • Security best practices analysis
    • Code review and improvements
    • API documentation in structured format
  • 🎯 Custom template support for specialized use cases
  • 📊 Multiple output formats (text, markdown, JSON)
  • 🔍 Optional source URL inclusion in responses
  • ⚙️ Configurable model parameters (temperature, max tokens)
  • 🚀 Support for various Perplexity models including Sonar and LLaMA

Configuration

This server requires configuration through your MCP client. Here are examples for different environments:

Cline Configuration

Add this to your Cline MCP settings:

{
	"mcpServers": {
		"mcp-perplexity-search": {
			"command": "npx",
			"args": ["-y", "mcp-perplexity-search"],
			"env": {
				"PERPLEXITY_API_KEY": "your-perplexity-api-key"
			}
		}
	}
}

Claude Desktop with WSL Configuration

For WSL environments, add this to your Claude Desktop configuration:

{
	"mcpServers": {
		"mcp-perplexity-search": {
			"command": "wsl.exe",
			"args": [
				"bash",
				"-c",
				"source ~/.nvm/nvm.sh && PERPLEXITY_API_KEY=your-perplexity-api-key /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-perplexity-search"
			]
		}
	}
}

Environment Variables

The server requires the following environment variable:

  • PERPLEXITY_API_KEY: Your Perplexity API key (required)

API

The server implements a single MCP tool with configurable parameters:

chat_completion

            Generate chat completions using the Perplexity API with support for

specialized prompt templates.

Parameters:

  • messages (array, required): Array of message objects with:
    • role (string): 'system', 'user', or 'assistant'
    • content (string): The message content
  • prompt_template (string, optional): Predefined template to use:
    • technical_docs: Technical documentation with code examples
    • security_practices: Security implementation guidelines
    • code_review: Code analysis and improvements
    • api_docs: API documentation in JSON format
  • custom_template (object, optional): Custom prompt template with:
    • system (string): System message for assistant behaviour
    • format (string): Output format preference
    • include_sources (boolean): Whether to include sources
  • format (string, optional): 'text', 'markdown', or 'json' (default: 'text')
  • include_sources (boolean, optional): Include source URLs (default: false)
  • model (string, optional): Perplexity model to use (default: 'sonar')
  • temperature (number, optional): Output randomness (0-1, default: 0.7)
  • max_tokens (number, optional): Maximum response length (default: 1024)

Development

Setup

  1. Clone the repository
  2. Install dependencies:
pnpm install
  1. Build the project:
pnpm build
  1. Run in development mode:
pnpm dev

Publishing

The project uses changesets for version management. To publish:

  1. Create a changeset:
pnpm changeset
  1. Version the package:
pnpm changeset version
  1. Publish to npm:
pnpm release

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see the LICENSE file for details.

Acknowledgments

Last updated: 4/5/2025

Publisher info

spences10's avatar

Scott Spence

I've never Svelte like this before!

@XtendOps-developers
London, United Kingdom
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